Naive Bayes Predictor

Predicts the class per row based on the learned model. The class
probability is the product of the probability per attribute and the
probability of the class attribute itself.

The probability for nominal values is the number of occurrences of
the class value with the given value divided by the number of total
occurrences of the class value. The probability of numerical values
is calculated by assuming a normal distribution per attribute.

Options

Change prediction column name

When set, you can change the name of the prediction column.(The
default is: Prediction (trainingColumn).)

Append columns with normalized class distribution

If selected a column is appended for each class instance with the
normalized probability of this row being member of this class.

Suffix for probability columns

Suffix for the normalized distribution columns. Their names are like:
P (trainingColumn=value).

Input Ports

A previously learned naive Bayes model

Input data to classify

Output Ports

The input table with one column added containing the
classification and the probabilities depending on the options.

Installation

To use this node in KNIME, install
KNIME Core
from the following update site:

KNIME 4.0

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